Frame the problem
Identify the expensive workflow, define the decision or outcome that matters, and agree on what success can be observed.
Consulting
Focused help for difficult engineering systems.
I take on narrowly scoped engagements where experienced engineering judgment and hands-on implementation can materially change the outcome. Work is fixed-fee based on scope, not billed as an open-ended block of hours.
The flagship engagement
AI for engineering operations
Move a valuable internal workflow from idea or prototype to a controlled system that the team can operate.
Inspect the system
Review architecture, data, permissions, operational constraints, and the failure modes the design must respect.
Build the useful thing
Implement the smallest production-worthy system that materially improves the workflow—not a disconnected demo.
Evaluate and harden
Test usefulness and failure behavior, add observability and guardrails, and make human control explicit.
Hand it over
Document the system, transfer operational knowledge, and leave the client team able to own and extend it.
Representative work
Examples, not rigid packages.
The final scope follows the problem and the client environment. These are common starting points.
01
AI for engineering operations
Design and build controlled AI systems that work with the operational context engineers already depend on.
- A high-value workflow selected against clear success criteria
- Tool and MCP integrations with explicit permission boundaries
- Grounding, evaluation, observability, and human approval
- Production-ready implementation, documentation, and handoff
02
Engineering workflow automation
Remove repetitive operational work with the right mix of deterministic automation and carefully bounded AI.
- Workflow and engineering-friction review
- Automation architecture with ownership and failure handling
- Implementation across CI/CD, incident, or internal workflows
- Runbooks, measurements, and maintainable team handoff
03
Observability & telemetry systems
Improve signal quality, operating usefulness, and cost without turning telemetry into another platform teams have to fight.
- Architecture, instrumentation, and ingestion review
- Actionable alert and dashboard design
- Sampling, retention, and cost-control changes
- Standards, configuration changes, and ownership model
04
Production reliability review
Find the operational and architectural risks that are expensive to discover during an incident.
- Architecture and failure-mode analysis
- Incident-history and scaling-risk review
- Disaster-recovery and observability gap analysis
- Prioritized remediation plan for engineering leadership
A strong fit
The problem is important, bounded, and owned.
The best engagements have an engineering sponsor, access to the people and systems needed to understand the problem, and a result that matters enough to implement properly.
I am not the right fit for generic staff augmentation, commodity application development, or projects looking for an autonomous system to replace operational accountability.
Have a difficult production problem that does not fit one of the examples? Describe it. A custom technical engagement may be the better shape.
Start a conversation
Have an expensive engineering problem?
Tell me what you are dealing with. If it is within my area of experience, I will tell you whether I think I can materially help.